Biomedical subjects

Philip W Fowler

Publications and source records attributed to Philip W Fowler.

5 recordsLinked to original sources

PubMed2025

Evaluating 12 automated, whole-genome sequencing analysis pipelines for Mycobacterium tuberculosis complex: a comparative study.

BACKGROUND: Reliance on complex, custom-built bioinformatics pipelines is a barrier to the implementation of whole-genome sequencing (WGS) of Mycobacterium tuberculosis in high-burden settings in some low-income and middle-income countries (LMICs). Automated analysis pipelines could address this inequity in access to WGS-based diagnostics and surveillance. This study aimed to systematically evaluate the performance and usability of publicly available WGS pipelines for M tuberculosis. METHODS: We identified automated M tuberculosis WGS analysis pipelines through searches of PubMed and GitHub from database inception up to Aug 31, 2024. Accuracy, cost, accessibility, and scalability were assessed for each pipeline. We evaluated the accuracy of genotypic drug susceptibility testing (gDST) using publicly available sequences with phenotypic susceptibility data for 12 antituberculosis drugs. We estimated pooled sensitivity and specificity for each pipeline, across all drugs, by conducting a bivariate meta-analysis, with random effects representing between-drug variability. Lineage classifications were compared, and a previously epidemiologically well-characterised dataset was used to compare measures of genomic relatedness. FINDINGS: Among 28 candidate pipelines, 16 were excluded as they were unmaintained and inexecutable. 12 pipelines (11 compatible with Illumina and four compatible with Nanopore), all free to use, were included for evaluation. Six pipelines processed and stored data remotely, but for five of these six, scalability was limited by the need to upload sequences through web portals. For local processing pipelines, scalability was dependent on substantial local computational resources, data storage capacity, and command-line interfaces that limited user-friendliness. Only one of six remote-processing pipelines removed human DNA sequences before server upload. gDST was similarly accurate across ten of 11 Illumina-compatible pipelines and three of four Nanopore-compatible pipelines. All pipelines classified the main lineages consistently, although there were differences at sublineage resolution. Outputs from three of four pipelines reporting genomic relatedness were compatible with commonly cited single nucleotide polymorphism difference thresholds. INTERPRETATION: Numerous automated analysis pipelines capable of enhancing equity in M tuberculosis WGS are available. Given the overall similarities between the pipelines evaluated in this study in terms of gDST performance, lineage classification, and genomic relatedness inference, non-functional attributes such as availability, accessibility, scalability, and privacy could represent the point of difference for prospective users in LMICs with a high burden of tuberculosis. FUNDING: The Rhodes Trust, Wellcome, Ellison Institute of Technology, and the UK National Institute for Health and Care Research Oxford Biomedical Research Centre.

Mycobacterium tuberculosis↗

PubMed2006

A computational protocol for the integration of the monotopic protein prostaglandin H2 synthase into a phospholipid bilayer.

Prostaglandin H2 synthase (PGHS) synthesizes PGH2, a prostaglandin precursor, from arachidonic acid and was the first monotopic enzyme to have its structure experimentally determined. Both isozymes of PGHS are inhibited by nonsteroidal antiinflammatory drugs, an important class of drugs that are the primary means of relieving pain and inflammation. Selectively inhibiting the second isozyme, PGHS-2, minimizes the gastrointestinal side-effects. This had been achieved by the new PGHS-2 selective NSAIDs (i.e., COX-2 inhibitors) but it has been recently suggested that they suffer from additional side-effects. The design of these drugs only made use of static structures from x-ray crystallographic experiments. Investigating the dynamics of both PGHS-1 and PGHS-2 using classical molecular dynamics is expected to generate new insight into the differences in behavior between the isozymes, and therefore may allow improved PGHS-2 selective inhibitors to be designed. We describe a molecular dynamics protocol that integrates PGHS monomers into phospholipid bilayers, thereby producing in silico atomistic models of the PGHS system. Our protocol exploits the vacuum created beneath the protein when several lipids are removed from the top leaflet of the bilayer. The protein integrates into the bilayer during the first 5 ns in a repeatable process. The integrated PGHS monomer is stable and forms multiple hydrogen bonds between the phosphate groups of the lipids and conserved basic residues (Arg, Lys) on the protein. These interactions stabilize the system and are similar to interactions observed for transmembrane proteins.

Algorithms↗

PubMed2005

Modelling biological complexity: a physical scientist's perspective.

We discuss the modern approaches of complexity and self-organization to understanding dynamical systems and how these concepts can inform current interest in systems biology. From the perspective of a physical scientist, it is especially interesting to examine how the differing weights given to philosophies of science in the physical and biological sciences impact the application of the study of complexity. We briefly describe how the dynamics of the heart and circadian rhythms, canonical examples of systems biology, are modelled by sets of nonlinear coupled differential equations, which have to be solved numerically. A major difficulty with this approach is that all the parameters within these equations are not usually known. Coupled models that include biomolecular detail could help solve this problem. Coupling models across large ranges of length- and time-scales is central to describing complex systems and therefore to biology. Such coupling may be performed in at least two different ways, which we refer to as hierarchical and hybrid multiscale modelling. While limited progress has been made in the former case, the latter is only beginning to be addressed systematically. These modelling methods are expected to bring numerous benefits to biology, for example, the properties of a system could be studied over a wider range of length- and time-scales, a key aim of systems biology. Multiscale models couple behaviour at the molecular biological level to that at the cellular level, thereby providing a route for calculating many unknown parameters as well as investigating the effects at, for example, the cellular level, of small changes at the biomolecular level, such as a genetic mutation or the presence of a drug. The modelling and simulation of biomolecular systems is itself very computationally intensive; we describe a recently developed hybrid continuum-molecular model, HybridMD, and its associated molecular insertion algorithm, which point the way towards the integration of molecular and more coarse-grained representations of matter. The scope of such integrative approaches to complex systems research is circumscribed by the computational resources available. Computational grids should provide a step jump in the scale of these resources; we describe the tools that RealityGrid, a major UK e-Science project, has developed together with our experience of deploying complex models on nascent grids. We also discuss the prospects for mathematical approaches to reducing the dimensionality of complex networks in the search for universal systems-level properties, illustrating our approach with a description of the origin of life according to the RNA world view.

Animals↗

PubMed2005

Grid-based steered thermodynamic integration accelerates the calculation of binding free energies.

The calculation of binding free energies is important in many condensed matter problems. Although formally exact computational methods have the potential to complement, add to, and even compete with experimental approaches, they are difficult to use and extremely time consuming. We describe a Grid-based approach for the calculation of relative binding free energies, which we call Steered Thermodynamic Integration calculations using Molecular Dynamics (STIMD), and its application to Src homology 2 (SH2) protein cell signalling domains. We show that the time taken to compute free energy differences using thermodynamic integration can be significantly reduced: potentially from weeks or months to days of wall-clock time. To be able to perform such accelerated calculations requires the ability to both run concurrently and control in realtime several parallel simulations on a computational Grid. We describe how the RealityGrid computational steering system, in conjunction with a scalable classical MD code, can be used to dramatically reduce the time to achieve a result. This is necessary to improve the adoption of this technique and further allows more detailed investigations into the accuracy and precision of thermodynamic integration. Initial results for the Src SH2 system are presented and compared to a reported experimental value. Finally, we discuss the significance of our approach.

Computer Graphics↗

PubMed2005

Large scale molecular dynamics simulation of native and mutant dihydropteroate synthase-sulphanilamide complexes suggests the molecular basis for dihydropteroate synthase drug resistance.

Antibiotic resistance is hampering the efficacy of drugs in the treatment of several pathological infections. Dihydropteroate synthase (DHPS) has been targeted by sulphonamide inhibitors for the past 60 years and has developed different amino acid mutations to survive sulpha drug action. We couple homology modelling techniques and massively parallel molecular dynamics simulations to study both the drug-bound and apo forms of native and mutant DHPS. Simulations of the complex between sulphanilamide and Streptomyces pneumoniae, DHPS shows how sulphanilamide is able to position itself close to 6-hydroxymethyl-7, 8-dihydropteridine-phosphate in a suitable position for the enzymatic transformation whereas in the mutant complex the sulpha drug is expelled from the catalytic site. Our simulations, therefore, provide insight into the molecular basis for drug resistance with S. pneumoniae DHPS.

Anti-Bacterial Agents↗